Background <p>The rapid rise of robot-assisted surgery (RAS), especially with the Da Vinci Surgical System (DVSS), has transformed surgical practices, enhanced precision and improving patient outcomes. As this technology becomes more prevalent, operating room nurses have taken on more specialized roles. However, there is a lack of standardized training and competency evaluation for these nurses, leading to inconsistencies in their preparedness.</p> Aim <p>The current study aimed at developing a competency evaluation index system for nurses in RAS: a Delphi study.</p> Methods <p>This study employed a modified Delphi method to develop a competency evaluation index system for nurses in RAS. The study was conducted across seven tertiary-level hospitals in China, all equipped with the Da Vinci Surgical System. Three groups of participants were involved: nursing educators and managers, surgeons, and an expert panel. Data were collected through a literature review, semi-structured interviews, and two rounds of Delphi expert consultations. The importance of competency indicators was measured using a 5-point Likert scale in the survey.</p> Results <p>The positive coefficient of experts in both rounds of the Delphi survey was 100%, with an authority coefficient of 0.9125, the Kendall’s coordination coefficients of the first, second, and third level indexes were 0.467, 0.324, and 0.260 (<i>P</i> &lt; 0.001), 0.454, 0.257, and 0.331 (<i>P</i> &lt; 0.001). The final index system includes three primary indicators (basic nursing Competencies, specialty nursing competencies and comprehensive application capabilities), twelve secondary indicators, and sixty-seven tertiary indicators.</p> Conclusion <p>This study established a structured competency evaluation framework for nurses in robot-assisted surgery, comprising three primary, twelve secondary, and sixty-seven tertiary indicators. This system serves as a foundational tool for assessing professional competencies and provides a reference for designing targeted training programs.</p> Recommendation <p>Future research should focus on converting the indicators into a scale for wider use, further validating its effectiveness and practicality.</p> Clinical trial number <p>Not applicable.</p>